• Journal of Software Engineering Society
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• v.27 no.1
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• pp.1-7
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• 2018

The consumption of mobile device batteries which are limited resources is an important criterion when circuit designers analyze and evaluate circuits. For this reason, researchers conducted researches with different models of battery consumption to analyze power consumption of mobile devices. The battery consumption model generation techniques have various characteristics depending on availability of sensors, run-time model generation, and models for using in verification and testing. However, there is lack of comparison and analysis between varied battery consumption model generation methods. In this research, we compare and evaluate the analysis methods which have been studied so far to support the circuit investigation for circuit designers. Finally, we suggest the direction of researches in battery consumption analysis using the comparison result.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.43 no.10 s.352
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• pp.134-139
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• 2006

In this paper we present the Low-Power Bus Driven Floorplan(BDF) in which the bus power consumption is minimized by using a new cost function. The previously reported BDF has used the cost function which minimizes only the chid and the bus area. However, such a cost function may not consider the bus power consumption determined by the topology of a bus in case of the segmented bus design. In this paper, we formulate a new cost function which. reflects the communication frequency and the real distance between blocks in a bus to model the bus power consumption. For the Low-Power BDF with the new cost function, the experimental results show the bus power consumption cost is reduced by 11.43% on the average.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.9B
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• pp.1322-1329
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• 2010

As body sensor network (BSN) research becomes mature, the need for managing power consumption of sensor nodes has become evident since most of the applications are designed for continuous monitoring. Real time Electrocardiograph (ECG) analysis on sensor nodes is proposed as an optimal choice for saving power consumption by reducing data transmission overhead. Smart sensor nodes with the ability to categorize lately detected ECG cycles communicate with base station only when ECG cycles are classified as abnormal. In this paper, ECG classification algorithms are described, which categorize detected ECG cycles as normal or abnormal, or even more specific cardiac diseases. Our Euclidean distance (ED) based classification method is validated to be most power efficient and very accurate in determining normal or abnormal ECG cycles. A close comparison of power efficiency and classification accuracy between our ED classification algorithm and generalized linear model (GLM) based classification algorithm is provided. Through experiments we show that, CPU cycle power consumption of ED based classification algorithm can be reduced by 31.21% and overall power consumption can be reduced by 13.63% at most when compared with GLM based method. The accuracy of detecting NSR, APC, PVC, SVT, VT, and VF using GLM based method range from 55% to 99% meanwhile, we show that the accuracy of detecting normal and abnormal ECG cycles using our ED based method is higher than 86%.

• Journal of Korean Institute of Industrial Engineers
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• v.7 no.1
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• pp.21-31
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• 1981

This paper develops a short term forecasting model for household electric power consumption in Seoul, which can be used for the effective planning and control of utility management. The model developed is based on exponentially weighted moving average model and incorporates monthly average temperature as an exogeneous factor so as to enhance its forecasting accuracy. The model is empirically compared with the Winters' three parameter model which is widely used in practice and the Box-Jenkins model known to be one of the most accurate short term forecasting techniques. The result indicates that the developed hybrid exponential model is better in terms of accuracy measured by average forecast error, mean squared error, and autocorrelated error.

• The KIPS Transactions:PartD
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• v.19D no.4
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• pp.281-292
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• 2012

A wide variety of smartphone applications is increasing the usage time of smartphone. Due to the increased time, it becomes difficult to providing stable services to users with limited battery capacity. The past works have been performed the power management of mobile device toward long-lasting battery development or low-power electric devices. However as the complexity of software embedded into system are increased, the research interests of the software power analysis is also increased. Among these studies on the software power analysis, model-based analysis technique is one of major interests because it can be able to analyze the power consumption before the development of source codes, then the analysis result can be used in the development of the software system, This paper suggests a model-based power analysis technique using UML state machine diagram. Our proposed technique estimates the power consumption by the simulation of Perti-net which is transformed from the state machine diagram.

• Environmental and Resource Economics Review
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• v.23 no.2
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• pp.349-364
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• 2014

This study analyzed Granger causality between power consumption and production activity in manufacturing sector, by using error correction model. It found that there exists the connection between power consumption and production activity in manufacturing sector. By reflecting the industrial characteristics, it found not only the bilateral causality (power consumption ${\leftrightarrow}$ production activity) in power non-intensive industry, high value-added industry and low value-added industry, but also one-way causality (power consumption ${\rightarrow}$ production activity) in power-intensive industry. These results imply that power demand management policy focusing on efficiency improvement is necessary primarily to minimize negative impacts on production activity, and also stable power supply system is required to meet the increase of power demand.

• International Journal of Aerospace System Engineering
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• v.3 no.2
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• pp.26-30
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• 2016

Experimental study on the unsteady aerodynamics analysis and power consumption of a folding wing is accomplished using a wind tunnel testing. A folding wing model is fabricated and actuated using servo motors. The flapping wing consists of an inboard main wing and an outboard folding wing. The aerodynamic forces and consumed powers of the flapping wing are measured by changing the flapping and folding wings inside a low-speed wind tunnel. In order to calculate the aerodynamic forces, the measured forces are modified using static test data. It was found that the effect of the folding wing on the flapping wing's total lift is small but the effect of the folding wing on the total thrust is larger than the main wing. The folding motion requires the extra use of the servo motor. Thus, the amount of the energy consumption increases when both the wings are actuated together. As the flight speed increases, the power consumption of the folding wing decreases which results in energy saving.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.63 no.4
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• pp.307-311
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• 2014

Due to the increasing of power consumption, it is difficult to construct accurate prediction model for daily peak power demand. It is very important work to know power demand in next day for manager and control power system. In this research, we develop a daily peak power demand prediction method considering of characteristics of day of week. The proposed method is composed of liner model based on AR model and nonlinear model based on ELM to resolve the limitation of a single model. Using data sets between 2006 and 2010 in Korea, the proposed method has been intensively tested. As the prediction results, we confirm that the proposed method makes it possible to effective estimate daily peak power demand than conventional methods.

• Journal of Korea Game Society
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• v.17 no.4
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• pp.137-148
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• 2017

Since the power consumption of data centers is large and computer serves take a large portion of it, there have been much research on the power saving of servers in various ways recently. Among the units of severs CPU is one of major power consuming units. In this paper, a method of client-server assignment for minimizing the CPU power consumption of servers in a game server cluster is proposed. We model the client-server assignment problem as an optimization problem, and find a solution to the problem using a simulated annealing-based technique. One of major features of our method is to select a proper operating frequency according to the amount of load on a server. The selection of a lower frequency in case of low load will result in reducing power consumption. To our survey, little research on client-server assignment in consideration of power consumption has been carried out.

• Journal of IKEEE
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• v.20 no.2
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• pp.163-166
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• 2016

It is important to operate the driving circuit under the optimal condition through precisely sensing the power consumption causing the temperature made mainly by the MOSFET (metal-oxide semiconductor field-effect transistor) when a BLDC (Brushless Direct Current) motor operates. In this letter, a Super-junction (SJ) power TMOSFET (trench metal-oxide semiconductor field-effect transistor) with an ultra-low specific on-resistance of $0.96m{\Omega}{\cdot}cm^2$ under the same break down voltage of 100 V is designed by using of the SILVACO TCAD 2D device simulator, Atlas, while the specific on-resistance of the traditional power MOSFET has tens of $m{\Omega}{\cdot}cm^2$, which makes the higher power consumption. The SPICE simulation for measuring the power distribution of 25 cells for a chip is carried out, in which a unit cell is a SJ Power TMOSFET with resistor arrays. In addition, the power consumption for each unit cell of SJ Power TMOSFET, considering the number, pattern and position of bonding, is computed and the power distribution for an ANSYS model is obtained, and the SJ Power TMOSFET is designed to make the power of the chip distributed uniformly to guarantee it's reliability.